Search Results (229)

The geometric foundations of General Relativity are revisited here, with particular attention to its gauge invariance, as a key to understanding the true nature of spacetime. Beyond the common image of spacetime as a deformable “fabric” filling the Universe, curvature is interpreted as the dynamic interplay between matter and interacting fields, a view already emphasized by Einstein and Weyl but sometimes overlooked in the literature. Building on these tools, a Newtonian framework is reconstructed that captures essential aspects of cosmology, showing how classical intuition can coexist with modern geometric insights. This perspective shifts the focus from substance to relationships, offering a fresh magnifying glass through which to reinterpret gravitational dynamics and the large-scale structure of the Universe. The similarities of this approach with other recent, more ambitious ones carried out at the quantum level are quite remarkable. Full article

Access to practice opportunities for history-taking in undergraduate medical education can be resource-limited. Large language models are a potential avenue to address this. This study sought to characterize changes in learner self-reported confidence with history-taking before and after a simulation with an LLM-based patient and understand learner experience with and the acceptability of virtual LLM-based patients. This was a multi-method study conducted at McMaster University. Simulations were facilitated with the OSCEai tool. Data was collected through surveys with a Likert scale and open-ended questions and semi-structured interviews. A total of 24 participants generated 93 survey responses and 17 interviews. Overall, participants reported a 14.6% increase in comfort with history-taking. Strengths included its flexibility, accessibility, detailed feedback, and ability to provide a judgement-free space to practice. Limitations included its lower fidelity compared to standardized patients and at times repetitive and less clinically relevant feedback as compared to preceptors. It was overall viewed best as a supplement rather than a replacement for standardized patients. In conclusion, LLM-based virtual patients were feasible and valued as an adjunct tool. They can support scalable, personalized practice. Future work is needed to understand objective metrics of improvement and to design curricular strategies for integration. Full article

Urban green spaces are essential for promoting human health and well-being, especially in cities facing increasing noise pollution and ecological stress. This study investigates the effects of audio-visual interaction on restorative outcomes across three soundscape types (park, residential, and street), focusing on the compensatory role of positive visual stimuli in low-quality soundscape environments. Thirty-two university students participated in a controlled evaluation using soundscapes and corresponding visual materials derived from 30 urban green spaces. A two-way repeated measures ANOVA revealed significant main effects of soundscape type and modality (auditory vs. audio-visual), as well as a significant interaction between these factors. Audio-visual conditions consistently outperformed auditory conditions, with the strongest restorative effects observed in noisy street soundscapes when paired with positive visual stimuli. Further analysis highlighted that visual cleanliness and structural clarity significantly enhanced restorative outcomes in challenging environments. These findings align with existing theories of sensory integration and extend their application to large-scale urban settings. This study shows that multi-sensory optimization can mitigate urban environmental stressors, supporting healthier, more resilient, and sustainable urban environments. Future research should explore long-term and cross-cultural applications to inform evidence-based urban planning and public health policies. Full article

We present a quantitative theory of contraction and expansion cycles within the Quantum Memory Matrix (QMM) cosmology. In this framework, spacetime consists of finite-capacity Hilbert cells that store quantum information. Each non-singular bounce adds a fixed increment of imprint entropy, defined as the cumulative quantum information written irreversibly into the matrix and distinct from coarse-grained thermodynamic entropy, thereby providing an intrinsic, monotonic cycle counter. By calibrating the geometry–information duality, inferring today’s cumulative imprint from CMB, BAO, chronometer, and large-scale-structure constraints, and integrating the modified Friedmann equations with imprint back-reaction, we find that the Universe has already completed $N_{\mathrm{past}}=3.6\pm 0.4$ cycles. The finite Hilbert capacity enforces an absolute ceiling: propagating the holographic write rate and accounting for instability channels implies only $N_{\mathrm{future}}=7.8\pm 1.6$ additional cycles before saturation halts further bounces. Integrating Kodama-vector proper time across all completed cycles yields a total cumulative age $t_{\mathrm{QMM}}=62.0\pm 2.5\mathrm{Gyr}$, compared to the $13.8\pm 0.2\mathrm{Gyr}$ of the current expansion usually described by $\mathrm{\Lambda }$CDM. The framework makes concrete, testable predictions: an enhanced faint-end UV luminosity function at $z\gtrsim 12$ observable with JWST, a stochastic gravitational-wave background with $f^{2/3}$ scaling in the LISA band from primordial black-hole mergers, and a nanohertz background with slope $\alpha \simeq 2/3$ accessible to pulsar-timing arrays. These signatures provide near-term opportunities to confirm, refine, or falsify the cyclical QMM chronology. Full article

The land used for fruit cultivation now exceeds 120 million hectares globally, with an annual yield of nearly 940 million tons. Fruit picking, the most labor-intensive task in agricultural production, is gradually shifting toward automation using intelligent robotic systems. As the component in direct contact with crops, specialized picking end-effectors perform well for certain fruits but lack adaptability to diverse fruit types and canopy structures. This limitation has constrained technological progress and slowed industrial deployment. The diversity of fruit shapes and the wide variation in damage thresholds—2–4 N for strawberries, 15–40 N for apples, and about 180 N for kiwifruit—further highlight the challenge of universal end-effector design. This review examines two major technical pathways: separation mechanisms and grasping strategies. Research has focused on how fruits are detached and how they can be securely held. Recent advances and limitations in both approaches are systematically analyzed. Most prototypes have achieved picking success rates exceeding 80%, with average cycle times reduced to 4–5 s per fruit. However, most designs remain at Technology Readiness Levels (TRLs) 3–5, with only a few reaching TRLs 6–7 in greenhouse trials. A dedicated section also discusses advanced technologies, including tactile sensing, smart materials, and artificial intelligence, which are driving the next generation of picking end-effectors. Finally, challenges and future trends for highly universal agricultural end-effectors are summarized. Humanoid picking hands represent an important direction for the development of universal picking end-effectors. The insights from this review are expected to accelerate the industrialization and large-scale adoption of robotic picking systems. Full article

Culture-led urban regeneration represents a potent strategy for revitalizing post-industrial cities but necessitates navigating complex property rights fragmentation and competing stakeholder interests. This research interrogates how different institutional arrangements mediate this process, balancing economic development with cultural preservation and social sustainability. Through a comparative case study of two seminal projects in Xi’an, China—the Yisu Opera Society and the Old Food Market—this paper examines the divergent outcomes of two property rights reconfiguration strategies: land assembly and rights subdivision. Findings reveal a fundamental trade-off: while the land assembly model facilitates efficient, large-scale redevelopment and economic revitalization, it often precipitates gentrification and the erosion of socio-cultural fabric. Conversely, the rights subdivision approach, though incurring higher ongoing transaction costs, fosters more equitable and embedded regeneration by preserving community networks and authentic character. Grounded in Property Rights and Transaction Cost theories, this study con-structs an analytical framework to evaluate how governance structures, stakeholder dynamics, and contextual factors shape project outcomes. The research concludes that there is no universal solution; the optimal pathway depends on the specific heritage context and social embeddedness of a site. It contributes to urban scholarship by highlighting the critical role of flexible, hybrid governance models in managing urban complexity and offers practical policy insights for designing regeneration frameworks that can more equitably distribute the benefits of urban development. Full article

Background/Objectives: Organized physical activity is frequently considered a protective factor against bullying behaviors, yet evidence within the university context remains limited. This study investigates the relationships between physical activity levels, body mass index (BMI), and involvement in traditional and digital bullying, taking into account the differences between students with and without structured sports training. Methods: A total of 2767 first-year students from Transylvania University of Brașov participated. The sports group (n = 161; 65 females, 96 males) was compared to the non-sports group (n = 2606; 1472 females, 1134 males). Instruments included the Physical Activity Questionnaire for Adolescents (PAQ-A), validated scales for traditional and cyberbullying and victimization, and BMI calculation. Statistical analyses involved t-tests (two-tailed), 2 × 2 factorial ANOVA, and sex-stratified multiple linear regressions. Results: Students with sports training reported higher physical activity (PAQ-A 4.2–4.6), lower BMI, and lower bullying involvement (traditional ≈ 14–21% vs. ≈32%; cyber ≈ 8–17% vs. ≈25%). Group differences were large for physical activity (Hedges’ g ≈ 1.5) and moderate for BMI and bullying (g ≈ 0.68–0.96; point-biserial r² ≈ 3–4%). ANOVA showed sports status main effects (partial η_p² ≈ 4–5% for bullying/BMI; ≈20% for PAQ-A). In regressions, sports status (B = −0.30 to −0.44) and physical activity (B = −0.22 to −0.32) predicted lower aggression/victimization, whereas BMI showed positive associations (B = 0.11 to 0.18) (all p < 0.001). Sex × sports interactions were significant for PAQ-A and for traditional and cyber-victimization. Conclusions: Structured physical activity contributes to reducing the risk of bullying involvement and supports better psychosocial adjustment among students. These findings underscore the educational and preventive potential of university sports programs. Full article

This study investigated shifts in preservice teachers’ perceived preparedness, readiness to engage in the profession, and teaching self-efficacy before and after a culminating field experience within a two-year, master’s level initial teacher education program at a large Australian university. Employing the Pre-service Teacher Professional Experience (PTPE) scale, we examined pre-service teachers’ pre- and post-field experience changes for each construct. We then used structural equation modeling to test a hypothesized causal framework, confirming theorized relationships among preparedness, readiness to engage, and self-efficacy for teaching. Path analyses revealed significant shifts in how specific dimensions of preparedness contributed to preservice teachers’ readiness to engage in the profession, which, in turn, influenced their teaching self-efficacy. Findings support the utility of the PTPE and causal framework in future research on teacher preparation, particularly as a means for teacher education programs to assess pre-service teacher development in alignment with professional standards for teaching. Full article

The process of galaxy evolution over cosmic time is not yet fully understood, since there is a debate on the impact of galaxy collisions on the star formation and metallicity. The local environment of the galaxy mergers could also have a large impact on the evolution of the galaxies, but it has not yet been possible to examine it in detail. Modern simulations with larger capacity, including the newest physical knowledge and new observations with JWST, help us to answer these questions. Using the IllustrisTNG cosmological simulation, we processed the catalogue data and the merger tree files of the TNG300-1 simulation. We calculated the galaxies’ average star formation rate (SFR) and mass at redshifts between 0 < z < 15. We investigated the environment of galaxy mergers, with the focus on the local density, and also examined how the SFR changes in merging galaxies. We compared our findings with JWST results and highlighted differences in the star formation rate density (SFRD) history between the models and observations. Full article

Evaluating the restoration quality of university outdoor spaces is often constrained by subjective surveys and manual assessment, limiting scalability and objectivity. This study addresses this gap by applying explainable machine learning to predict restorative quality from campus imagery, enabling large-scale, data-driven evaluation and capturing complex nonlinear relationships that traditional methods may overlook. Using Fujian Agriculture and Forestry University as a case study, this study extracted road network data, generated 297 coordinates at 50-m intervals, and collected 1197 images. Surveys were conducted to obtain restorative quality scores. The Mask2Former model was used to extract landscape features, and decision tree algorithms (RF, XGBoost, GBR) were selected based on MAE, MSE, and EVS metrics. The combination of optimal algorithms and SHAP was employed to predict restoration quality and identify key features. This research also used a multivariate linear regression model to identify features with significant statistical impact but lower features importance ranking. Finally, the study also analyzed heterogeneity in scores for three restoration indicators and five campus zones using k-means clustering. Empirical results show that natural elements like vegetation and water positively affect psychological perception, while structural components like walls and fences have negative or nonlinear effects. On this basis, this study proposes spatial optimization strategies for different campus areas, offering a foundation for creating high-quality outdoor environments with restorative and social functions. Full article

Most astrophysical systems (except for very compact objects such as, e.g., black holes and neutron stars) in our Universe are characterized by shallow gravitational potentials, with dimensionless compactness $|\Phi |\equiv r_s/R\ll 1$, where $r_s$ and R are their Schwarzschild radius and typical size, respectively. While the existence and characteristic scales of such virialized systems depend on gravity, we demonstrate that the value of $|\Phi |$—and thus the non-relativistic nature of most astrophysical objects—arises from microphysical parameters, specifically the fine structure constant and the electron-to-proton mass ratio, and is fundamentally independent of the gravitational constant, G. In fact, the (generally extensive) gravitational potential becomes ‘locally’ intensive at the system boundary; the compactness parameter corresponds to the binding energy (or degeneracy energy, in the case of quantum degeneracy pressure-supported systems) per proton, representing the amount of work that needs to be done in order to allow proton extraction from the system. More generally, extensive properties of gravitating systems depend on G, whereas intensive properties do not. It then follows that peak rms values of large-scale astrophysical velocities and escape velocities associated with naturally formed astrophysical systems are determined by electromagnetic and atomic physics, not by gravitation, and that the compactness, $|\Phi |$, is always set by microphysical scales—even for the most compact objects, such as neutron stars, where $|\Phi |$ is determined by quantities like the pion-to-proton mass ratio. This observation, largely overlooked in the literature, explains why the Universe is not dominated by relativistic, compact objects and connects the relatively low entropy of the observable Universe to underlying basic microphysics. Our results emphasize the central but underappreciated role played by dimensionless microphysical constants in shaping the macroscopic gravitational landscape of the Universe. In particular, we clarify that this independence of the compactness, $|\Phi |$, from G applies specifically to entire, virialized, or degeneracy pressure-supported systems, naturally formed astrophysical systems—such as stars, galaxies, and planets—that have reached equilibrium between self-gravity and microphysical processes. In contrast, arbitrary subsystems (e.g., a piece cut from a planet) do not exhibit this property; well within/outside the gravitating object, the rms velocity is suppressed and G reappears. Finally, we point out that a clear distinction between intensive and extensive astrophysical/cosmological properties could potentially shed new light on the mass hierarchy and the cosmological constant problems; both may be related to the large complexity of our Universe. Full article

This article presents a case of strategic and participatory institutional innovation in higher education, focused on developing teacher digital competence (TDC) as a key enabler of sustainable digital transformation. In response to the post-pandemic challenges faced by the National University of Cuyo (UNCuyo), a large and multi-campus public university in Argentina, the European CUTE methodology was adapted and implemented to align professional development with institutional planning. Grounded in the DigCompEdu framework, this action-oriented process moved beyond individual initiatives to create a coordinated, multi-level strategy involving educators, department leaders, and university authorities. Through a research-based design that included context analysis, participatory diagnosis, and co-designed interventions, the project built a shared understanding of digital teaching needs and institutional readiness. The implementation highlights how locally adapted frameworks, collaborative structures, and iterative decision-making can drive meaningful change across a complex university system. This case contributes to the international conversation on how higher education institutions can operationalize innovation at scale by investing in teacher competence, inclusive processes, and strategic alignment. Lessons learned from this experience are relevant for universities seeking to build institutional capacity for digital transformation in diverse educational contexts with potential downstream benefits for student learning and inclusion. Full article

Background/Objectives: International students pursuing higher education in the United States face unique challenges that increase their risk of food insecurity, including limited financial resources, employment restrictions, and cultural barriers. While food insecurity among domestic students has been widely studied, limited research focuses on the lived experiences of international graduate students. This study explores the challenges, perceptions, and coping strategies related to food insecurity among international graduate students at a large public university in North Texas. Methods: This qualitative, ethnographic study involved 20 semi-structured interviews with international graduate students who were clients of the university’s food pantry. Participants were recruited using purposive convenience sampling. Interviews focused on students’ experiences with food access, financial constraints, campus resources, and cultural food preferences. Data were analyzed using thematic coding in MAXQDA. Two standardized food insecurity measures—the USDA and FAO scales—were also administered and analyzed using SPSS. Results: Findings revealed that 85% of participants experienced limited access to nutritious and culturally appropriate foods, with 70% reporting hunger due to financial constraints. Themes included lack of cooking skills, limited campus food options, difficulty accessing familiar groceries, and limited job opportunities. Students expressed that food insecurity significantly impacted their physical health, mental well-being, and social lives, though many continued to prioritize academics over personal nourishment. Conclusions: Food insecurity among international graduate students is multifaceted, shaped by financial, cultural, and institutional barriers. Addressing this issue requires culturally sensitive interventions, improved access to diverse food options, tailored student support services, and institutional efforts to better understand and meet the needs of international students. Full article

Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID) regulations require drones to broadcast critical flight information such as velocity, access to large-scale, high-quality broadcast data remains limited. To address this, this study leverages a Digital Twin (DT) framework to augment Remote ID spatio-temporal broadcasts, emulating the sensing environment of dense urban airspace. Using Remote ID data, we propose BiDGCNLLM, a hybrid prediction framework that integrates a Bidirectional Graph Convolutional Network (BiGCN) with Dynamic Edge Weighting and a reprogrammed Large Language Model (LLM, Qwen2.5–0.5B) to capture spatial dependencies and temporal patterns in drone speed trajectories. The model forecasts near-future speed variations in surrounding drones, supporting proactive conflict avoidance in constrained air corridors. Results from the AirSUMO co-simulation platform and a DT replica of the Cranfield University campus show that BiDGCNLLM outperforms state-of-the-art time series models in short-term velocity prediction. Compared to Transformer-LSTM, BiDGCNLLM marginally improves the $R^2$ by 11.59%. This study introduces the integration of LLMs into dynamic graph-based drone prediction. It shows the potential of Remote ID broadcasts to enable scalable, real-time airspace safety solutions in UAM. Full article

Constraining neutrino mass through cosmological observations relies on precise simulations to calibrate their effects on large scale structure, while these simulations must overcome computational challenges like dealing with large velocity dispersions and small intrinsic neutrino perturbations. We present an efficient N-body implementation with semi-linear neutrino mass response which gives accurate power spectra and halo statistics. We explore the necessity of correcting the expansion history caused by massive neutrinos and the transition between relativistic and non-relativistic components. The above method of including neutrino masses is built into the memory-, scalability-, and precision-optimized parallel N-body simulation code CUBE 2.0. Through a suite of neutrino simulations, we precisely quantify the neutrino mass effects on the nonlinear matter power spectra and halo statistics. Full article